




'''simple docstring'''



import requests
from bsa import BeautifulSoup







def       _UpperCamelCase			(_lowerCamelCase				:  str ,						_lowerCamelCase				:  dict						)-> str:




     '''simple docstring'''





     __snake_case            =	BeautifulSoup(requests.get(_lowerCamelCase ,						params=_lowerCamelCase						).content ,						'''html.parser'''						)
     __snake_case            =	soup.find('''div''' ,						attrs={'''class''': '''gs_ri'''}						)
     __snake_case            =	div.find('''div''' ,						attrs={'''class''': '''gs_fl'''}						).find_all('''a'''						)
     return anchors[2].get_text()


if __name__ == "__main__":
     UpperCAmelCase_							:	Optional[Any]	     =		{
         '''title''': (
             '''Precisely geometry controlled microsupercapacitors for ultrahigh areal '''
             '''capacitance, volumetric capacitance, and energy density'''
         ),
         '''journal''': '''Chem. Mater.''',
         '''volume''': 3_0,
         '''pages''': '''3979-3990''',
         '''year''': 2_0_1_8,
         '''hl''': '''en''',
     }
     print(get_citation('''https://scholar.google.com/scholar_lookup''', params=params))









from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


__snake_case				:      int   		=			{
    """configuration_llama""": ["""LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LlamaConfig"""],
}

try:
	if not is_sentencepiece_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__snake_case				:      int   		=			["""LlamaTokenizer"""]

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__snake_case				:      int   		=			["""LlamaTokenizerFast"""]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__snake_case				:      Union[str, Any]   		=			[
	    """LlamaForCausalLM""",
	    """LlamaModel""",
	    """LlamaPreTrainedModel""",
	    """LlamaForSequenceClassification""",
	]


if TYPE_CHECKING:
	from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

	try:
		if not is_sentencepiece_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_llama import LlamaTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_llama_fast import LlamaTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
	import sys

	__snake_case				:      Dict   		=			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


